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Mentor's Seminar

2023/2024
Учебный год
ENG
Обучение ведется на английском языке
1
Кредиты
Статус:
Курс обязательный
Когда читается:
1-й курс, 1-4 модуль

Преподаватели

Course Syllabus

Abstract

The mentor's seminar is intended for joint activities of the academic mentor and the student to solve the following tasks: determining individual educational results that the student intends to achieve during the development of the program; selection and coordination of academic disciplines, relevant projects and seminars; individual consultation of the student with the mentor about the progress of the program and the degree of achievement of results; adjustment of the individual curriculum in the case of of necessity.
Learning Objectives

Learning Objectives

  • The aim of this seminar is to support students in building their individual learning trajectories and defining individual educational outcomes.
Expected Learning Outcomes

Expected Learning Outcomes

  • To take ethical approach to work in international and multicultural teams
  • Students can choose and formulate appropriate directions of their research, evaluate their practical value and theoretical contribution
  • Able to identify soft and data skills relevant to a particular business area
  • Able to implement sustainable development principles in research projects
Course Contents

Course Contents

  • Introduction to the Master's program and data analytics
  • Sustainable development goals in management and economics
  • Skills for analysts
  • Term paper discussion
Assessment Elements

Assessment Elements

  • non-blocking Class participation
    Participation in class discussion and completion the questionnaire
  • non-blocking Group presentation
    the topic is "Soft and data skills in data analytics"
  • non-blocking Class participation
    Individual or group discussion after the term papaer's pre-defence.
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    0.3 * Group presentation + 0.4 * Class participation + 0.3 * Class participation
Bibliography

Bibliography

Recommended Core Bibliography

  • UI AHSAAN, S., & MOURYA, A. K. (2019). Big Data Analytics: Challenges and Technologies. Annals of the Faculty of Engineering Hunedoara - International Journal of Engineering, 17(4), 75–79.

Recommended Additional Bibliography

  • Pyne, S., Prakasa Rao, B. L. S., & Rao, S. B. (2016). Big Data Analytics : Methods and Applications. New Delhi, India: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1281845